Community health scoring tool

ABSTRACT

A system and method for scoring and comparing communities includes the development of community health measures by on combining and supplementing healthcare data and community data from numerous sources. The community health measures may be stored in a community health measures database and may be accessed by interactive tools to generate customized representations of healthcare measures for selected communities. The representations are automatically computed in response to interactive user selections. Geographic map representation, heat map representations and data tables may be automatically generated to identify correlations between health outcomes and population attributes in different communities.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application claims the priority of U.S. Provisional PatentApplication No. 62/028,627 entitled COMMUNITY HEALTH SCORING TOOL whichwas filed on Jul. 24, 2014 and which is incorporated herein by referencein its entirety. The present application also claims the priority ofU.S. Provisional Patent Application No. 62/048,082 entitled COMMUNITYHEALTH SCORING TOOL which was filed on Sep. 9, 2014 and which isincorporated herein by reference in its entirety.

FIELD OF TECHNOLOGY

The present disclosure relates generally to health care informationprocessing and particularly to systems and frameworks for measuringhealth care resource distribution.

BACKGROUND

A large amount of consumer healthcare information is routinely collectedby healthcare providers, insurance providers, government agencies,researchers and other institutions. Even though much of the informationis stored electronically, analyzing the information to improve healthcare delivery generally involves extensive efforts to identifyappropriate data sources and to secure access to the data sources.Useful healthcare information may be stored on diverse computer networksand data storage systems, which may often be difficult or impossible toaccess for research purposes. Refining or expanding research efforts toanalyze different parameters may often involve repeated efforts toaccess different data sources. Due to these and other difficulties,useful data representations that are suitable to support decisions forhealthcare resource allocation in various communities have heretoforebeen scarce.

SUMMARY

A method for measuring community health care attributes according to anaspect of the present disclosure includes storing a first collection ofhealth care data in one or more electronic storage systems. The firstcollection includes a number of health outcomes for health careconsumers in a number of communities. The health care outcomes mayinclude measures of health care cost, health care quality, andpopulation health, for example.

A system for measuring health care related characteristics of apopulation segment according to another aspect of the present disclosureincludes one or more electronic data storage systems coupled inelectronic communication with one or more health care data sources. Thesystem also includes a community health care database stored in one ormore of the electronic data storage system(s) and one or more processorscoupled in electronic communication with the electronic data storagesystems. The community health care database includes a first collectionof health care data. The first collection includes health outcomes forhealth care consumers in a number of communities, in which the healthcare outcomes for each consumer are associated with one or more of thecommunities. A second collection of community data is also stored in theelectronic data storage system(s). The second collection includespopulation attributes that characterize the populations of healthcareconsumers, resources, infrastructure and/or environment in each of thecommunities. The processor(s) are configured for receiving a firstinteractive input that selects one or more of the health care outcomesand/or one or more of the population attributes, identifying acorrelation between the selected health care outcomes and one or more ofthe population attributes by accessing the first collection of healthcare data and the second collection of community data in response toreceiving the interactive inputs, and representing the correlation to auser.

A method of measuring community health care characteristics according toanother aspect of the present disclosure includes receiving one or morehealth care outcomes for each of a number of communities, automaticallyscoring each of the communities based on the corresponding health careoutcomes and displaying a representation of the communities arrangedbased on their score.

A method for measuring community health care attributes, according toanother aspect of the present disclosure includes storing a collectionof health care data in one or more electronic storage systems. Thecollection of health care data includes a health outcomes for healthcare consumers in a number of communities and/or population attributesof the communities. The method includes associating the health careoutcomes and/or population attributes for each consumer with one or moreof the communities to generate a community health care database.

Additional features and advantages of the present disclosure aredescribed below. It should be appreciated by those skilled in the artthat this disclosure may be readily utilized as a basis for modifying ordesigning other structures, systems and processes for carrying out thesame purposes of the present disclosure. It should also be realized bythose skilled in the art that such equivalent implementations do notdepart from the teachings of the disclosure as set forth in the appendedclaims. The novel features, which are believed to be characteristic ofthe disclosure, both as to its organization and method of operation,together with further objects and advantages, will be better understoodfrom the following description when considered in connection with theaccompanying figures. It is to be expressly understood, however, thateach of the figures is provided for the purpose of illustration anddescription only and is not intended as a definition of the limits ofthe present disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The particular features and advantages of the present disclosure will beapparent from the detailed description set forth below in conjunctionwith the drawings in which like reference characters identifycorresponding aspects throughout.

FIG. 1 shows a block diagram of a data communication system according toaspects of the present disclosure.

FIG. 2 is a block diagram of a system that can implement part or all ofone or more aspects or processes of systems to implement a communityhealth measures tool according to embodiments of the present disclosure.

FIGS. 3A and 3B are illustrations of an interactive user interfaceincluding user controls for generating a geographical map representationof community health measures according to aspects of the presentdisclosure.

FIGS. 4A and 4B are geographical representations of community healthmeasures generated according to aspects of the present disclosure.

FIGS. 5A and 5B are heat map representations of community healthmeasures generated according to aspects of the present disclosure.

FIG. 6 is a process flow diagram illustrating a method for measuringcommunity healthcare attributes according to aspects of the presentdisclosure.

FIG. 7 is a system block diagram illustrating a system for measuringhealth care related characteristics of a population segment according toaspects of the present disclosure.

DETAILED DESCRIPTION

The features and advantages of the present disclosure will becomeapparent from the following detailed description of illustrativeembodiments thereof, which is to be read in connection with theaccompanying drawings.

Computer systems may be coupled together in various ways to enablecommunications between them, including being coupled together innetworks such as local area networks (LANs), wide area networks (WANs),or combinations of networks, such as the Internet and world wide web.Data may be transferred (e.g., copied or moved) between computer systemsin various ways. For instance, an application executing at a firstcomputer system may generate a query, which is a request for particulardata. The query may be transmitted to a second computer system, whichcontains or has access to a data source containing the desired data. Thesecond computer system responds to the query by transmitting therequested data to the first computer system.

The present specification discloses one or more embodiments thatincorporate the features of the invention. The disclosed embodiment(s)merely exemplify the invention. The scope of the invention is notlimited to the disclosed embodiment(s). The invention is defined by theclaims appended hereto.

References in the specification to “one embodiment,” “an embodiment,”“an example embodiment,” etc., indicate that the embodiment describedmay include a particular feature, structure, or characteristic, butevery embodiment may not necessarily include the particular feature,structure, or characteristic. Moreover, such phrases are not necessarilyreferring to the same embodiment. Further, when a particular feature,structure, or characteristic is described in connection with anembodiment, it is submitted that it is within the knowledge of oneskilled in the art to effect such feature, structure, or characteristicin connection with other embodiments whether or not explicitlydescribed.

Aspects of the present disclosure relate to data communications indistributed systems. For example, FIG. 1 shows a block diagram of a datacommunication system 100, according to an example embodiment. As shownin FIG. 1, system 100 includes a first computer system 102, a secondcomputer system 104, a first storage 114, a network 116, and a secondstorage 118. An application 106 executes in first computer system 102.Storage 114 is coupled to first computer system 102. Storage 118 iscoupled to second computer system 104. First and second computer systems102 and 104 are communicatively coupled by network 116. System 100 isconfigured to enable resources to be transferred between first andsecond computer systems 102 and 104.

First and second computer systems 102 and 104 may each be any type ofcomputing device, including a desktop computer (e.g., a personalcomputer), a server, a mobile computer or computing device such as asmart phone or tablet computer device, a personal digital assistant(PDA), a laptop computer, a notebook computer, etc., or other type ofcomputer system. Storage 114 and storage 118 may each include one ormore of any type of storage mechanism to store content (e.g., objects),including a hard disk drive, an optical disc drive, a memory device suchas a RAM device, a ROM device, etc., and/or any other suitable type ofstorage medium.

Network 116 may include one or more communication links and/orcommunication networks, such as a LAN (local area network), a WAN (widearea network), or a combination of networks, such as the Internet. Firstand second communication links 122 and 124, which respectively couplefirst and second computer systems 102 and 104 to network 116, mayinclude any number of communication links, including wired and/orwireless links, such as IEEE 802.11 wireless LAN (WLAN) wireless links,Worldwide Interoperability for Microwave Access (Wi-MAX) links, cellularnetwork links, wireless personal area network (PAN) links (e.g.,Bluetooth™ links), Ethernet links, USB links, etc.

Application 106 may issue a query for a resource (e.g., data). Theresource may be accessible as data 108 contained in storage 118 atsecond computer system 104. To obtain the resource, first computersystem 102 may transmit the query from first computer system 102 in afirst communication signal 110. For example, first computer system 102may contain an agent (e.g., a “client” agent) configured to handletransmission of queries. First communication signal 110 is transmittedthrough a first communication link 122, network 116, and a secondcommunication link 124, and is received by second computer system 104.First communication signal 110 may be transmitted in any form, includingin the form of a stream of packets (e.g., IP packets).

Second computer system 104 processes the request received in firstcommunication signal 110. For example, second computer system 104 mayinclude an agent (e.g., a “server” agent) configured to process receivedqueries. Second computer system 104 retrieves data 108 from storage 118,which may contain a database or other data source. Second computersystem 104 generates a second communication signal 112, which is aresponse signal that includes data 108. Second communication signal 112is transmitted through second communication link 124, network 116, andfirst communication link 122, and is received by first computer system102. Application 106 receives data 108 included in second communicationsignal 112, which may be stored in storage 114 (as indicated by dottedlines in FIG. 1). Second communication signal 112 may be transmitted inany form, including in the form of a stream of packets (e.g., IPpackets).

Currently, applications and services are being developed that includethe use of REST (representational state transfer) interfaces foraccessing resources and a URI (Uniform Resource Identifier) namespacethat identifies the resources. These applications and services enableweb-based data sources to be accessed in a more efficient manner. Forexample, second computer system 104 in FIG. 1 may be configured to havea REST interface to enable data 108 to be accessed according a URI.

FIG. 2 is a block diagram of a system 200 that can implement part or allof one or more aspects or processes of systems within which a web-nativebridge according to embodiments of the present disclosure can operate orwithin which methods according to embodiments of the present disclosurecan be carried out. As shown in FIG. 2, memory 230 configures theprocessor 220 to implement one or more aspects of the methods, steps,and functions disclosed herein (collectively, shown as process 280 inFIG. 2). Different method steps can be performed by differentprocessors. The memory 230 could be distributed or local and theprocessor 220 could be distributed or singular. The memory 230 could beimplemented as an electrical, magnetic or optical memory, or anycombination of these or other types of storage devices. It should benoted that if distributed processors are employed, each distributedprocessor that makes up processor 220 generally contains its ownaddressable memory space. It should also be noted that some or all ofcomputer system 200 can be incorporated into an application-specific orgeneral-use integrated circuit. For example, one or more method stepscould be implemented in hardware in an ASIC rather than using firmware.Display 240 is representative of a variety of possible input/outputdevices (e.g., displays, touchscreens, mice, keyboards, and so on).

A system for measuring health care related characteristics of apopulation segment according to an aspect of the present disclosureincludes one or more electronic data storage systems coupled inelectronic communication to one or more health care data sources. Theelectronic data storage systems may be coupled to the health care datasources directly or indirectly by one or more different means forcommunication such as direct wiring, wireless communication, fiberoptics, and may involve communication via one or more intermediatecommunication network such as the Internet, for example. The health caredata sources may include various entities, groups or networks that areinvolved with the healthcare industry and which generate, receive and/orcollect healthcare related information. Healthcare data sources mayinclude healthcare providers, healthcare payers, researchers and/orgovernment agencies, for example.

Because a large amount of healthcare data may at times be subjectvarious strict privacy policies, regulations or statutes governing thestorage and communication private healthcare information, aspects of thepresent disclosure include systems that may not be configured in astandard technical environment using only standard communicationtechniques, conventional general purpose computer networks andcommunication equipment, for example. Rather, aspects of the presentdisclosure may provide substantial improvements to the conventionaltechnical environments for accessing, storing and/or communicatinghealthcare information include special purpose computer hardware,software, algorithms and/or communication techniques to de-identify dataand/or to ensure that healthcare data is accessed, communicated andstored in a manner that private healthcare data may include privatehealth information. For example, the system may include special purposecomputer hardware, software, algorithms and/or communication techniquesor portions thereof that may be implemented by only a small number ofhealthcare industry stakeholders such as healthcare payer and providernetworks to ensure data privacy.

According to aspects of the present disclosure, the system includes acommunity health care database stored in one or more of the electronicdata storage system(s) and one or more processors coupled in electroniccommunication with the electronic data storage systems. In thisimplementation, the community health care database includes a firstcollection of health care data. The first collection includes healthoutcomes for health care consumers in a number of communities, in whichthe health care outcomes for each consumer are associated with one ormore of the communities. A second collection of community data is alsostored in the electronic data storage system(s). The second collectionincludes population attributes that characterize the populations ofhealthcare consumers, resources, infrastructure and/or environment ineach of the communities. The processor(s) are configured for receiving afirst interactive input that selects one or more of the health careoutcomes and/or one or more of the population attributes, identifying acorrelation between the selected health care outcomes and one or more ofthe population attributes by accessing the first collection of healthcare data and the second collection of community data in response toreceiving the interactive inputs, and representing the correlation to auser.

According to an aspect of the present disclosure a database ofpreviously unavailable community healthcare measures is generated byaccessing sources of electronic healthcare data via communication linksto one or more healthcare networks, for example, processing a widevariety of the healthcare data to compute population health outcomes fornumerous communities and combing the population health outcomes withcommunity data from numerous data sources.

The community data describes a large number of communities in terms ofvarious population attributes. The population attributes includedemographic population characteristics of each community as well ashealthcare delivery system attributes for each community. The healthcaredelivery system attributes may characterize system of health care,healthcare infrastructure and environment, for example. Examples ofvarious population attributes that may be used to generate the disclosedhealthcare measures database according to aspects of the presentdisclosure are listed in Table 1.

TABLE 1 Population characteristics Delivery System Attributes SocialCapital Capacity Predicted mean health literacy Primary careproviders/100,000 % with basic health literacy or above SpecialisMDs/100,000 % high school graduates Hospital beds/1,000 Petris socialcapital Ambulatory centers/100,000 Per capita 501c3 revenues - regionalnon-profit Nurses/1000 activity PAs/1000 Aggregate social capital -emotional support Incentives % college graduates % hospitals withsalaried physician Economics arrangements Median household income Changein income % hospital revenues from capitations 2000 to 2009 Unemploymentrate Managed care penetration Employers and employment % hospitalrevenues at risk Demographics Integration and Alignment Race andethnicity (1% distribution) % % hospitals with CPHO physicianarrangements population living in rural area % hospitals with OPHOphysician arrangements Health behaviors: % physicians working inhospital owned practices Smoking rate % physicians working in healthsystem owned Chlamydia infections/1,000 practices Average lifeexpectancy % physicians working in large (50+) practices Obesity rate %physicians in solo practice % physicians in IPAs % hospitals with IPAsACO & PCMH coverage HIT % hospitals with electronic health records %hospitals with health information exchanges % hospitals with EMRsachieving MU % primary care providers receiving HIT incentive$

Examples of various healthcare outcomes that may be used to generate thedisclosed healthcare measures database according to aspects of thepresent disclosure are listed in Table 2.

TABLE 2 Preference-Sensitive (PS) Care: “choosing Appropriate Carewisely” Adherence to clinical guidelines - appropriate PScholecystectomy procedures/1,000 prescribing PS back surgeryprocedures/1,000 Adherence to clinical guidelines - Physician PShysterectomy for uterine fibroid procedures/ follow up 1,000 Adherenceto clinical guidelines - pregnancy lab PS lower extremity bypassprocedures/1,000 screening PS carotid endarterectomy procedures/1,000Adherence to clinical guidelines - testing PS angiographyprocedures/1,000 medication complications PS CABG procedures/1,000Adherence to clinical guidelines - screening PS high tech diagnosticimaging/1,000 chronic conditions PS prostatectomy procedures/1,000Medication Adherence (commercial) PS AAA procedures/1,000 Asthmamedication adherence PS pacemaker insertion procedures/1,000 Depressionmedication adherence PS PCI/PTCA procedures/1,000 CAD medicationadherence PS bone marrow/organ transplants/1,000 Diabetes medicationadherence PS C-section rate Hyperlipidemia medication adherence PSmastectomy/1,000 Hypertension medication adherence PS total kneereplacement procedures/1,000 Costs of Care - total and by site, type PSmitral-aortic valve procedures/1,000 Commercial costs - adjusted forage, gender, PS total shoulder replacement/1,000 and input prices PStotal hip replacement/1,000 Medicare costs adjusted for age, gender, andMedicare preference sensitive knee risk replacements/1,000 Prevalence ofdisease Medicare preference sensitive hip Prevalence depression/1,000replacements/1,000 Prevalence of lower back problems/1,000 Medicarepreference sensitive back surgery/ Prevalence of migraine 1,000Prevalence of COPD/1,000 Avoidable Care Prevalence of hypertension/1,000Readmissions rate - commercial Prevalence of diabetes/1,000 Avoidableadmissions/1,000, commercial Prevalence of CHF/1,000 Medicare avoidableadmissions Prevalence of ESRD/1,000 Medicare readmission rate Prevalenceof CAD/1,000 Avoidable ED visits/1,000 Utilization ED visits/1,000Office visits/1,000 Inpatient admissions

According to aspects of the present disclosure, a community may includea geographical area, a demographic group within a population, a group ofhealthcare providers or other stakeholders, for example.

The community health measures include measures of health care cost,healthcare quality and community characteristics. Examples of thecommunity characteristic that are combined with healthcare data togenerate community health measures according to aspects of the presentdisclosure include socioeconomic status, economic activity, economicgrowth, social capital, structure and capacity of healthcare deliverysystems, alignment of healthcare providers, incentives for healthcarestakeholders and adoption of healthcare information technology (HIT).

According to the present disclosure, the community healthcare measuresare constructed based on data received from a number of public sourcesand proprietary sources. In one example, data received from publicsources includes socioeconomic status (SES), economics, social capitalinformation that is extracted from census and from the AmericanCommunity Survey performed by the United States Census Bureau. Accordingto aspects of the present disclosure, measures of health outcomes andhealthcare costs are computed based on claims data that iselectronically compiled by insurance providers such as United HealthCareof Minnetonka, Minn. Other measures of healthcare outcomes and costs maybe computed based on data received from healthcare provider networks andmedical associations such as the American Hospital Association, forexample. Additional data for computing health outcomes and healthcarecosts may be received from primary data collection performed byaccountable care organizations in the community, for example. Accordingto aspects of the present disclosure, data from any one or combinationof these public and private data sources may be accessed to generatevarious health care measures.

The community health measures database that is generated according toaspects of the present disclosure may be used by stakeholders and policymakers in government and throughout the healthcare industry to improvehealthcare delivery by increasing efficiency of healthcare networks,improving allocation of healthcare resources, and enhancing development,testing and deployment of healthcare innovations.

According to aspects of the present disclosure, the disclosed communityhealth measures database is accessed to define and compute numerous newcommunity health measures including: a community health measure thatcharacterizes the structure of the delivery system; a community healthmeasure that characterize supply of medical providers; a communityhealth measure that characterize innovations in an organization of care;a community health measure that characterizes HIT adoption; a communityhealth measure that characterizes health care costs; a community healthmeasure that characterizes resource utilization; and a community healthmeasure that characterizes appropriate care in the commercial populationbased on analysis of health insurance data, for example.

According to another aspect of the present disclosure, the communityhealth measures database is incorporated in and/or accessed by acommunity health care measures tool. The community health measures toolleverages aspects of the community health measure database to generatepreviously unavailable representations of community health information.A community health measures tool according to aspects of the presentdisclosure may be implemented on personal computers, computer networksand/or mobile devices, for example.

One implementation of a community health measures tool according toaspects of the present disclosure includes a community measures scoringtool. The community healthcare scoring tool may be configured to scorecommunities based on their attainment of desirable health outcomesand/or based on availability of healthcare resources that attribute todesirable health outcomes, for example. Performance scores and rankingof the communities is computed by accessing and statistically processingselected population attributes of the communities in the communityhealth measures database.

According to an aspect of the present disclosure user-defined weightsfor particular population attributes and/or healthcare outcomes may bepredefined or received by interactive input to customize the rankingsaccording to user needs and criteria. In this implementation, users maydefine the weights to customize the computation and/or representation ofcommunity rankings. The community scores, rankings, and comparativesimilarity with respect to selected health outcomes and populationattributes may be interactively computed to support a wide range of anumber of business and clinical decisions.

A community health measures tool according to an aspect of the presentdisclosure includes a computer implemented application configured with agraphical user interface for receiving a selection and weighting ofcommunities, population attributes and/or healthcare outcomes, anddisplaying a representation of the selected communities, populationattributes and/or healthcare outcomes. The representation is computedand displayed by processing data in a healthcare measures database basedon the selections and weightings of communities, population attributesand/or healthcare outcomes.

In one example, the community measures scoring tool is configured torepresent community efficiency scores by receiving and/or computingcomposite healthcare input measures and composite health outcomes foreach of a number of communities based on the population attributes andhealth outcomes in the community health measures database. The compositehealthcare input measures and composite health outcome measures arestatistically processed to generate scores that represents an efficiencymeasure for each respective community.

According to aspects of the present disclosure, selected communityscores may be juxtaposed in a map display, represented in a table, orarranged in a heat map to identify similar communities, for example. Amap display according to aspects of the present disclosure may be colorcoded or shaded to represent selected community scores with respect toselected health outcomes and/or community attributes. In one example,the tool may be configured to display a color of a community on a map torepresent a number of standard deviations of the correspondingcommunity's score from a mean community score in a selected health caremeasure. In another example, the tool may be configured to display acolor of each community on a map to represent the percentile or decileof scores in all communities in which the respective communities scoredwith respect to a particular healthcare measure, for example. In tabledisplay according to aspect of the present disclosure may display a listof communities ranked by their score in a selected health care measure.

Alternatively the community measures scoring tool may be configured todisplay a heat map representation of community scores. The heat maprepresentation displays a color coded or shaded grid in which colorsand/or shading of grid elements represent relative scores attained byeach of a number of selected communities in each of a number of selectedhealth outcomes and/or population attributes. According to anotheraspect of the present disclosure, a clustering process may be used tocluster together certain healthcare outcomes and/or populationattributes. The clustering process may be used to generate a heat maprepresentation, which identifies factors that act similarly in aparticular group of communities, and which identifies communities thatare most similar to each other, for example.

Implementations of the disclosed community measures scoring tool may beused to identify communities that are similar or dissimilar with respectto selected healthcare outcomes and/or selected population attributes inthe community health measures database. The community measures scoringtool may be configured to represent similar or dissimilar communities byjuxtaposing geographical representations of scores for correspondingcommunities on a map display, and/or by displaying a table of similarand dissimilar communities, for example. Degrees of similarity ordissimilarity between a selected community and other communities may berepresented by different colors and/or different shading on a mapdisplay, or may be indicated as numerical scores in a table, forexample. This allows users to select a community, and determine what arethe other communities that are most similar or least similar to theselected community in terms of a range of health outcomes and/orpopulation attributes.

In one example according to an aspect of the present disclosure, aclinical translation and trial tool is configured to represent communitysimilarity scores to identify appropriate locations for piloting ortesting medical devices, drugs or other innovations. Favorable locationsfor piloting or testing a new drug or health care innovation may bechosen based on their likelihood of furnishing a sufficiently large testpopulation that is correlated to one or more selected attributes, forexample. The clinical translation and trial tool also helps stakeholderschose favorable locations for implementing innovations based onfavorable results of piloting or testing the innovation in a similarcommunity.

The tools and methods described herein enable healthcare stakeholderssuch as communities, government agencies, insurance companies, healthcare networks and/or health care plans to make appropriate decisions toincrease health care value. The tools and methods described herein maybe used to evaluate stakeholder performance with respect to certainactionable aspects of affecting cost and health care use compared andcompare the stakeholder's performance to certain benchmarks or to theperformance of other stakeholders, for example. By quantifying theperformance of stakeholders relative to a particular market segment, thestakeholders may improve assessments of their own market performanceversus market potential, for example.

The tools and methods described herein may also be used by healthcarestakeholders to evaluate how efficiently they are using availableresources to generate favorable healthcare outcomes. This allowsstakeholders to identify gaps in the distribution of key resources,improve resource allocation and identify actions that may be limitingtheir performance.

According to an aspect of the present disclosure, the community healthmeasures tool allows a user to select healthcare outcomes and/orpopulation attributes, and automatically displays a representation ofcorresponding community healthcare measures that allow the user toeasily recognize communities that stand out in terms of the selectedhealthcare outcomes and/or population attributes. The community healthmeasures tool also allows a user to select particular communities sothat measures of corresponding healthcare outcomes and populationattributes of the communities can be automatically displayed forcomparison on a geographical map, a table, and/or a heat map, forexample.

An example implementation of an interactive community health measuretool for identifying similar communities in terms of health careoutcomes and population attributes according to an aspect of the presentdisclosure is described with reference to FIG. 3A. The system includesone or more user input fields, such as lists, check boxes and sliders toreceive interactive input from a user and generates a representation ofcommunities having similar or dissimilar community health measures basedon the interactive input. In the example shown in FIG. 3A, a cityselection input field 302 and a state selection input field 304 allow auser to easily select a city and state as a base community for comparingwith other communities. A comparison basis selection input field 306allows a user to select whether health care outcomes or inputs or bothwill be used as a basis of comparison for computing degrees of communitysimilarity. The inputs may include population attributes that drivehealth care cost and quality in a community, for example. Populationattributes that may be used as inputs for comparison include healthbehaviors, provider supply, social capital economic performance,provider incentives, HIT adoption and provider integration, for example.According to an aspect of the present disclosure one or more sliders 308are provided to receive a weight selection for one or more of thepopulation attributes to be compared. This allows a user tointeractively assign greater weight to more important populationattributes and to assign less weight to less important populationattributes for generating the comparison and identifying communitiessimilar to the selected base community.

According to an aspect of the present disclosure, a representation ofcomparative communities 310 is automatically generated and displayedbased on the parameters selected in the input fields. The representation310 automatically updates in response to changes in any of the inputfields. The representation may include a geographic map display, a datatable or a heat map, for example. According to an aspect of the presentdisclosure, a display selection input field 312 allows a user to selectwhich type of representation to be displayed. In this example, therepresentation 310 shows that the communities highlighted in one colorare most similar to the selected community of Los Angeles in terms ofthe inputs that contribute to a health care result. The communities thatare highlighted in another color are the least similar to Los Angeles interms of the same inputs.

Another example implementation of an interactive community healthmeasures tool for identifying communities based on a selected healthmeasure is described with reference to FIG. 3B. An aggregate measuresselection input field 314 and an individual measures selection inputfield 316 allow a user to easily select a healthcare measures as a basisfor comparing communities on a representation 318. In this example theselected aggregate measure is a measure of preference sensitiveprocedures and the selected individual measure is a measure of high techdiagnostic imaging. A display limit field 320 allows a user to select anumber of communities to be represented on the representation 318. Aregion selection input field 322 and a geographic area type selectionfield 324 allow a user to select the geographical region to bedisplayed. The selection of displayed regions may be further refined bya hospital referral region (HRR) selection field 325.

According to an aspect of the present disclosure, a representation ofthe selected healthcare measures is automatically generated anddisplayed in a map representation 310 of the selected regions. Therepresentation of the selected healthcare measures may include a colorcoding and/or shading gradient of regions on the map representationbased on a level of the selected measure. A measures key 326 displays anassociation of the shading or color coding of displayed regions with acorresponding level or range of levels of the selected measure. In thisexample, the levels are percentiles of the selected measure. The levelsmay displayed in order of favorable levels or unfavorable levels basedon an order selection input field 328. A load data button 330 and aclear data button 332 allows users to clear the representation 318 andchange the displayed representation 318 based upon different inputselections.

An example implementation of an interactive community health measuretool to generate geographical map representations of healthcare measuresaccording to aspects of the present disclosure is described withreference to FIGS. 4A and 4B in which the displayed measures indicatecomparative population Medicare costs and commercial healthcare costs.Referring to FIG. 4A a first geographical map representation 402indicates communities that have relatively low population Medicarecosts. The first geographical map representation 402 is juxtaposed witha second geographical map representation 404 showing communities thathave relatively high population Medicare costs. Referring to FIG. 4B athird geographical map representation 406 displays communities that haverelatively low population commercial medical costs. The thirdgeographical map representation 406 is juxtaposed with fourthgeographical map representation 408 showing communities that haverelatively high population commercial costs. The comparative costs aredisplayed by color coding the communities based on their standarddeviation from mean community costs. These geographical maprepresentation allows health care policy makers and other stakeholdersto identify comparative high performing communities and comparativelylow performing communities for analyzing equity of resourcedistribution, identifying where certain opportunities or needs exist,and/or identifying where certain policies have a particular level ofeffect, for example.

The community health measures tool may be implemented to quicklygenerate custom geographical map representations of health care measuresby interactively selecting parameters for comparison from a vastdatabase of community healthcare measures. Examples of other geographicmap representations of community health measures generated according toaspects of the present disclosure include geographic map representationsof medication adherence, health system integration and technologyadoption, avoidable hospitalizations, prevalence of smokers andprevalence of particular illness, such as emphysema, for example.

An example implementation of an interactive community health measuretool to generate heat map representations of healthcare measuresaccording to aspects of the present disclosure is described withreference to FIGS. 5A and 5B. Referring to FIG. 5A, a first heat maprepresentation 502 includes an array of grid elements that are eachcolor coded to represent a scores for one of a number populationattributes and health outcomes for each of a number of correspondingcommunities. In this example, a first heat map representation 502includes communities 504 that are identified, using the community healthmeasures tool, as the fifty communities represented in a communityhealth measures database as having the lowest Medicare total costs. Thedisplayed population attributes 506 and health outcomes include measuresof Medicare costs and measure of commercial medical costs, for example.

Referring to FIG. 5B, a second heat map representation 508 includescommunities 510 that are identified, using the community health measurestool, as the fifty communities represented in the community healthmeasures database as having the lowest commercial medical costs. Thedisplayed population attributes 512 and health outcomes include measuresof Medicare costs and measure of commercial medical costs, for example.By analyzing the first heat map 502 and the second heat map 508, it maybe observed that communities having low Medicare costs often have highcommercial costs and vice versa.

According to aspects of the present disclosure, the heat mapfunctionality of the community health measures tool allows users tointeractively cluster together attributes/factors and identify whichattributes/factors that act similarly in a particular group ofcommunities, and to identify which communities are most similar to eachother, for example relative to other communities. The resulting heat maprepresentations can be used to identify patterns of data that areotherwise substantially undetectable.

To assist pattern recognition, various clustering techniques may beapplied to the information displayed in a heat map representation. InFIGS. 5A and 5B, brackets are displayed at the periphery of each heatmap representation 502, 508 to indicate groupings of the displayedcommunities 504, 510 and groupings of the displayed populationattributes and health outcomes 506, 502. In this example, the bracketsare automatically generated using a grouping algorithm. The informativeclustering patterns can be useful for improved hypothesis generation andaddressing disparities between communities, for example.

Clustering can be performed based on any number of the attributes in theCommunity Health Measures Project database. Examples of other heat maprepresentations of community health measures generated according toaspects of the present disclosure include representations differentcommunities in terms of ethnicity and income, for example.

Geographic map representations generated by the community healthmeasures tool may often be used together with heat map representationsgenerated by the community health measures tool according to aspects ofthe present disclosure. In some implementation the complementarygeographic map representations and heat map representations may providea more robust comparison of communities.

A method for measuring community health care attributes according to anaspect of the present disclosure is described with reference to FIG. 6.The method 600 includes storing a first collection of health care datain one or more electronic storage systems at block 602. The firstcollection includes a number of health outcomes for health careconsumers in a number of communities. The health care outcomes mayinclude measures of health care cost, health care quality, andpopulation health, for example.

At block 604, the method includes associating the health care outcomesfor each consumer with one or more of the communities to generate acommunity health care database. At block 606, the method includesstoring a second collection of community data in the one or moreelectronic data storage systems. The second collection includes a numberof population attributes that characterize the health care consumers ineach of the communities. The second collection may also include a numberof population attributes that characterizes health care providers ineach of the communities. The population attributes may include measureof social capital, economics, demographics, health behaviors, healthcare provider capacity, health care provider incentives, integration andalignment of health care providers, and health information technology,for example.

At block 608, the method includes identifying a correlation between oneor more of the health care outcomes and one or more of the populationattributes by accessing the first collection of health care data and thesecond collection of community data. At block 610, the method includesrepresenting the correlation to a user.

The method 600 for measuring community health care attributes may alsoinclude assigning an outcome rank to each of the health care outcomesbased on a predetermined hierarchy of outcomes to generate an enhancedcommunity health care database, and representing one or more of thecommunities in association with one or more corresponding outcome ranksassigned to a respective healthcare outcome in the respective community.

According to another aspect of the present disclosure, the method 600may also include assigning a population attribute rank to each of thepopulation attributes, and representing one or more of the communitiesbased on the ranking of one or more of the population attributesassociated with the respective communities. The method 600 may alsoinclude computing a correlation between selected health care outcomeswith selected population attributes and identifying similar communitiesbased on a result of the correlating.

According to another aspect of the present disclosure, the method 600may also include receiving an input that selects one or more of thepopulation attributes and/or one or more of the health care outcomes,and interactively computing the correlation in response to receiving theinput.

A system for measuring health care related characteristics of apopulation segment according to an aspect of the present disclosure isdescribed with reference to FIG. 7. The system 700 includes one or moreelectronic data storage systems 702 coupled to one or more health carenetworks 704. A community health care database is stored in theelectronic data storage system(s) 704. The community health caredatabase including a first collection of health care data 706. The firstcollection of health care data 706 includes a number of health outcomesfor health care consumers in a number of communities. The health careoutcomes for each consumer are associated with one or more of thecommunities. A second collection of community data 708 is also stored inone or more of the electronic data storage systems 704. The secondcollection of community data 708 includes a number of populationattributes that characterize the health care consumers in each of thecommunities. One or more processors 710 are coupled in electroniccommunication with the electronic data storage systems 704.

According to aspects of the present disclosure the processor(s) 710 areconfigured for receiving a first interactive input that selects one ormore of the health care outcomes and/or one or more of the populationattributes. The health care outcomes may include measures of health carecost, health care quality, and population health, for example. Thepopulation attributes may include measure of consisting of socialcapital, economics, demographics, health behaviors, health care providercapacity, health care provider incentives, integration and alignment ofhealth care providers, and health information technology, for example.

The processor(s) 710 may also be configured for identifying acorrelation between the selected health care outcomes and one or more ofthe population attributes by accessing the first collection of healthcare data and the second collection of community data in response toreceiving the interactive inputs, and representing the correlation to auser. According to an aspect of the present disclosure, the processor(s)710 may be configured to interactively compute the correlation inresponse to receiving the input.

According to an aspect of the present disclosure, the processor(s) 710may also be configured to assign a population attribute rank to each ofthe population attributes, and represent one or more of the communitiesbased on the ranking of one or more of the population attributesassociated with the respective communities. The processor(s) 710 mayalso be configured to assign an outcome rank to each of the health careoutcomes based on a predetermined hierarchy of outcomes to generate anenhanced community health care database and represent one or more of thecommunities in association with one or more corresponding outcome ranksassigned to a respective healthcare outcome in the respective community.According to another aspect of the present disclosure, the processor(s)710 may be configured to identify similar communities based on a resultof the correlating.

Another aspect of the present disclosure includes a method of measuringcommunity health care characteristics. According to this aspect, themethod includes receiving one or more health care outcomes for each of anumber of communities, automatically scoring each of the communitiesbased on the corresponding health care outcomes, and displaying arepresentation of the communities arranged based on their score. Themethod may also include receiving one or more population attributes thatcharacterize the health care consumers in each of the communities, anddisplaying in indication of the corresponding population attributes inthe representation of the communities.

According to one aspect of the present disclosure, the method includesreceiving an input that selects one or more of the population attributesand one or more of the health care outcomes; and interactivelydisplaying a geographical representation of a relationship between theselected population attributes and the selected health care outcomes inresponse to receiving the input. According to another aspect of thepresent disclosure, the method includes receiving an input that selectsa number of the population attributes, and interactively displaying aheat map representation of health care measures based on the selectedpopulation attributes for each of a number of communities in response toreceiving the input. The method may also include generating clusteringinformation defining relationships between the displayed health caremeasures and rearranging the heat map representation based on theclustering information.

A method for measuring community health care attributes according toanother aspect of the present disclosure includes storing a firstcollection of health care data in one or more electronic storage systemsand associating the health care outcomes for each consumer with one ormore of the communities to generate a community health care database.The first collection includes a number of health outcomes for healthcare consumers in a number of communities. The method may also includeidentifying a correlation between a first one of the health careoutcomes associated with a community and a second one of the health careoutcomes associated with the community. The method then includesrepresenting the correlation to a user.

According to an aspect of the present disclosure, the method formeasuring community health care attributes may also include storing asecond collection of community data in the one or more electronic datastorage systems. The second collection may include a number ofpopulation attributes that characterize the health care consumers ineach of the communities and/or a number of population attributes thatcharacterizes health care providers in each of the communities, forexample. According to one aspect of the present disclosure, the methodincludes identifying a correlation between a first one of the populationattributes and a second one of the population attributes andrepresenting the correlation to a user. According to another aspect ofthe present disclosure, the method includes identifying a correlationbetween one or more of the health care outcomes and one or more of thepopulation attributes by accessing the first collection of health caredata and the second collection of community data and representing thecorrelation to a user.

The method may also include statistically processing the health careoutcomes to generate a number of categories of health care outcomesand/or statistically processing the population attributes to generate anumber of categories of population attributes. According to one aspectof the present disclosure, the health care outcomes are grouped into anumber of categories, including measures of health care cost, measuresof health care quality, and measures of population health, for example.According to another aspect of the present disclosure, the populationattributes are grouped into a number of categories including measure ofsocial capital, measures of economics, measures of demographics,measures of health behaviors, measures of health care provider capacity,measures of health care provider incentives, measures of integration ofhealth care providers, measures of alignment of health care providers,and measures of health information technology, for example.

The method for measuring community health care attributes may alsoinclude assigning an outcome score to each of the health care outcomesbased on a predetermined hierarchy of outcomes and computing a compositeoutcome score for each community by statistically combining the outcomescores in each community respective community. The method may alsoinclude representing one or more of the communities based a respectivecomposite outcome score of the respective communities.

According to another aspect of the present disclosure, the methodincludes assigning a population attribute score to each of thepopulation attributes, and computing a composite population attributescore for each community by statistically combining the populationattribute scores in each respective community. The method may alsoinclude representing one or more of the communities based on thecomposite population attribute score of the respective communities. Themethod may also include computing a community efficiency score bystatistically comparing the composite population attribute score of thecommunity with the composite outcome score of the community. Forexample, the method may include computing community efficiency scoresfor each of a number of communities by statistically comparing thecomposite population attribute score of each of the communities with thecomposite outcome score of each respective one of the communities anddisplaying the community efficiency scores for each of the communities.

According to an aspect of the present disclosure, the method includesdisplaying a geographical representation of a relationship betweenselected health outcomes and/or selected population attributes.According to another aspect of the present disclosure, the methodincludes displaying a heat map representation of health care measuresbased on selected health care outcomes and/or selected populationattributes. The heat map representation includes a composite outcomescore indication and/or a composite population attribute scoreindication for each of a number of the communities. The method may alsoinclude computing clustering information that defines relationshipsbetween the displayed health care measures and rearranging the heat maprepresentation based on the clustering information.

A method for measuring community health care attributes according toanother aspect of the present disclosure includes storing a firstcollection of community data in the one or more electronic data storagesystems. The first collection including a number attributes thatcharacterize health care consumers in each of a number of communities.The method also includes associating the attributes that characterizethe health care consumers with one or more of the communities togenerate a health care community population attribute database,identifying a correlation between a first one of the attributes in acommunity and a second one of the attributes in the community byaccessing the health care community population attribute database andrepresenting the correlation to a user.

The terms “computer program medium” and “computer usable medium” areused to generally refer to media such a as removable storage drive and ahard disk installed in a hard disk drive. These computer programproducts provide software to a computer system.

Computer programs (also referred to as computer control logic) arestored in main memory and/or secondary memory. Computer programs mayalso be received via communications interface. Such computer programs,when executed, enable the computer system to perform the features asdiscussed herein. In particular, the computer programs, when executed,enable the processor to perform the features of various embodiments.Accordingly, such computer programs represent controllers of thecomputer system.

In various embodiments, software may be stored in a computer programproduct and loaded into a computer system using removable storage drive,hard disk drive or communications interface. The control logic(software), when executed by the processor, causes the processor toperform the functions of various embodiments as described herein. Invarious embodiments, software may be implemented in hardware componentssuch as application specific integrated circuits (ASICs). Implementationof the hardware state machine so as to perform the functions describedherein will be apparent to persons skilled in the relevant art(s).

The system contemplates uses in association with web services, utilitycomputing, pervasive and individualized computing, security and identitysolutions, autonomic computing, cloud computing, commodity computing,mobility and wireless solutions, open source, biometrics, grid computingand/or mesh computing.

Databases discussed herein may include relational, hierarchical,graphical, or object-oriented structure and/or any other databaseconfigurations. Common database products that may be used to implementthe databases include DB2 by IBM (Armonk, N.Y.), various databaseproducts available from Oracle Corporation (Redwood Shores, Calif.),Microsoft Access or Microsoft SQL Server by Microsoft Corporation(Redmond, Wash.), MySQL by MySQL AB (Uppsala, Sweden), or any othersuitable database product. Moreover, the databases may be organized inany suitable manner, for example, as data tables or lookup tables. Eachrecord may be a single file, a series of files, a linked series of datafields or any other data structure. Association of certain data may beaccomplished through any desired data association technique such asthose known or practiced in the art. For example, the association may beaccomplished either manually or automatically. Automatic associationtechniques may include, for example, a database search, a databasemerge, GREP, AGREP, SQL, using a key field in the tables to speedsearches, sequential searches through all the tables and files, sortingrecords in the file according to a known order to simplify lookup,and/or the like. The association step may be accomplished by a databasemerge function, for example, using a “key field” in pre-selecteddatabases or data sectors. Various database tuning steps arecontemplated to optimize database performance. For example, frequentlyused files such as indexes may be placed on separate file systems toreduce In/Out (“I/O”) bottlenecks.

One skilled in the art will also appreciate that, for security reasons,any databases, systems, devices, servers or other components of thesystem may consist of any combination thereof at a single location or atmultiple locations, wherein each database or system includes any ofvarious suitable security features, such as firewalls, access codes,encryption, decryption, compression, decompression, and/or the like.

The computers discussed herein may provide a suitable website or otherInternet-based graphical user interface which is accessible by users. Invarious embodiments, the Microsoft Internet Information Server (IIS),Microsoft Transaction Server (MTS), and Microsoft SQL Server, are usedin conjunction with the Microsoft operating system, Microsoft NT webserver software, a Microsoft SQL Server database system, and a MicrosoftCommerce Server. Additionally, components such as Access or MicrosoftSQL Server, Oracle, Sybase, Informix MySQL, Interbase, etc., may be usedto provide an Active Data Object (ADO) compliant database managementsystem. In various embodiments, the Apache web server is used inconjunction with a Linux operating system, a MySQL database, and thePHP, and/or Python programming languages.

Any of the communications, inputs, storage, databases or displaysdiscussed herein may be facilitated through a website having web pages.The term “web page” as it is used herein is not meant to limit the typeof documents and applications that might be used to interact with theuser. For example, a typical website might include, in addition tostandard HTML documents, various forms, Java applets, JavaScript, activeserver pages (ASP), common gateway interface scripts (CGI), extensiblemarkup language (XML), dynamic HTML, cascading style sheets (CSS), AJAX(Asynchronous Javascript And XML), helper applications, plug-ins, andthe like. A server may include a web service that receives a requestfrom a web server, the request including a URL(http://yahoo.com/stockquotes/ge) and an IP address (123.56.789.234).The web server retrieves the appropriate web pages and sends the data orapplications for the web pages to the IP address. Web services areapplications that are capable of interacting with other applicationsover a communications means, such as the Internet. Web services aretypically based on standards or protocols such as XML, SOAP, AJAX, WSDLand UDDI, Web services methods are well known in the art, and arecovered in many standard texts. See, e.g., ALEX NGHIEM, IT WEB SERVICES:A ROADMAP FOR THE ENTERPRISE (2003), hereby incorporated by reference.

Middleware may include any hardware and/or software suitably configuredto facilitate communications and/or process transactions betweendisparate computing systems. Middleware components are commerciallyavailable and known in the art. Middleware may be implemented throughcommercially available hardware and/or software, through custom hardwareand/or software components, or through a combination thereof. Middlewaremay reside in a variety of configurations and may exist as a standalonesystem or may be a software component residing on the Internet server.Middleware may be configured to process transactions between the variouscomponents of an application server and any number of internal orexternal systems for any of the purposes disclosed herein. WebSphere MQ™(formerly MQSeries) by IBM, Inc. (Armonk, N.Y.) is an example of acommercially available middleware product. An Enterprise Service Bus(“ESB”) application is another example of middleware.

As will be appreciated by one of ordinary skill in the art, the systemmay be embodied as a customization of an existing system, an add-onproduct, a processing apparatus executing upgraded software, astand-alone system, a distributed system, a method, a data processingsystem, a device for data processing, and/or a computer program product.Accordingly, any portion of the system or a module may take the form ofa processing apparatus executing code, an internet based embodiment, anentirely hardware embodiment, or an embodiment combining aspects of theinternet, software and hardware. Furthermore, the system may take theform of a computer program product on a computer-readable storage mediumhaving computer-readable program code means embodied in the storagemedium. Any suitable computer-readable storage medium may be utilized,including hard disks, CD-ROM, optical storage devices, magnetic storagedevices, and/or the like.

The system and method is described herein with reference to screenshots, block diagrams and flowchart illustrations of methods, apparatus(e.g., systems), and computer program products according to variousembodiments. It will be understood that each functional block of theblock diagrams and the flowchart illustrations, and combinations offunctional blocks in the block diagrams and flowchart illustrations,respectively, can be implemented by computer program instructions.

These computer program instructions may be loaded onto a general purposecomputer, special purpose computer, or other programmable dataprocessing apparatus to produce a machine, such that the instructionsthat execute on the computer or other programmable data processingapparatus create means for implementing the functions specified in theflowchart block or blocks. These computer program instructions may alsobe stored in a computer-readable memory that can direct a computer orother programmable data processing apparatus to function in a particularmanner, such that the instructions stored in the computer-readablememory produce an article of manufacture including instruction meanswhich implement the function specified in the flowchart block or blocks.The computer program instructions may also be loaded onto a computer orother programmable data processing apparatus to cause a series ofoperational steps to be performed on the computer or other programmableapparatus to produce a computer-implemented process such that theinstructions which execute on the computer or other programmableapparatus provide steps for implementing the functions specified in theflowchart block or blocks.

Accordingly, functional blocks of the block diagrams and flowchartillustrations support combinations of means for performing the specifiedfunctions, combinations of steps for performing the specified functions,and program instruction means for performing the specified functions. Itwill also be understood that each functional block of the block diagramsand flowchart illustrations, and combinations of functional blocks inthe block diagrams and flowchart illustrations, can be implemented byeither special purpose hardware-based computer systems which perform thespecified functions or steps, or suitable combinations of specialpurpose hardware and computer instructions. Further, illustrations ofthe process flows and the descriptions thereof may make reference touser windows, webpages, websites, web forms, prompts, etc. Practitionerswill appreciate that the illustrated steps described herein may comprisein any number of configurations including the use of windows, webpages,web forms, popup windows, prompts and the like. It should be furtherappreciated that the multiple steps as illustrated and described may becombined into single webpages and/or windows but have been expanded forthe sake of simplicity. In other cases, steps illustrated and describedas single process steps may be separated into multiple webpages and/orwindows but have been combined for simplicity.

Benefits, other advantages, and solutions to problems have beendescribed herein with regard to specific embodiments. However, thebenefits, advantages, solutions to problems, and any elements that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as critical, required, or essentialfeatures or elements of the disclosure. The scope of the disclosure isaccordingly to be limited by nothing other than the appended claims, inwhich reference to an element in the singular is not intended to mean“one and only one” unless explicitly so stated, but rather “one ormore”.

Although illustrative embodiments of the present disclosure have beendescribed herein with reference to the accompanying drawings, it is tobe understood that the present disclosure is not limited to thoseprecise embodiments, and that various other changes and modificationsmay be made by one skilled in the art without departing from the scopeor spirit of the disclosure.

What is claimed is:
 1. A method implemented on a data processing systemmeasuring community health care attributes determined from diverse datastores, the method comprising: storing, by the data processing system, afirst collection of health care data in one or more electronic storagesystems, the first collection including a plurality of health careoutcomes for health care consumers in a plurality of communities;associating, by a data processing system, the health care outcomes foreach consumer with one or more of the communities to generate acommunity health care database; storing, by the data processing system,a second collection of community data in the one or more electronic datastorage systems, the second collection including a plurality ofpopulation attributes that characterize the health care consumers ineach of the communities; receiving, by the data processing system, aninput that selects one or more of the population attributes and/or oneor more of the health care outcomes; interactively computing, by thedata processing system, a correlation between one or more of the healthcare outcomes and one or more of the population attributes in responseto receiving the input; identifying, by the data processing system, thecorrelation by accessing the first collection of health care data andthe second collection of community data to provide correlated data;processing, by the data processing system, the correlated data using acommunity measures tool, comprising: generating, by the communitymeasures tool, a visual representation of the correlated data to a user,the visual representation comprising a heat map representation of healthcare measures having a color coded or shaded grid identifying similarcommunities based on a result of the correlation; generating, by acommunity measures scoring tool of the community measures tool, acommunity score for the plurality of communities; receiving, by acomputer implemented application of the community measures tool,user-defined weights for one or more of the population attributes and/orone or more of the health care outcomes to customize the visualrepresentation and/or community score to the user, the applicationincluding a graphical user interface adapted to receive the user-definedweights; automatically updating, by the community measures tool, thevisual representation of the correlated data in response to changes tothe user-defined weights from the graphical user interface; receiving,by the community measures tool, a user input that selects one or more ofthe plurality of communities; and displaying, by the community measurestool, corresponding healthcare outcomes and population attributes of theselected communities from the user input that selects one or more of theplurality of communities on the visual representation for comparisonbetween each community.
 2. The method of claim 1, wherein the secondcollection further includes a plurality of population attributes thatcharacterizes a system of health care, a health care infrastructure,and/or a health care environment in each of the communities.
 3. Themethod of claim 1, further comprising: assigning an outcome rank to eachof the health care outcomes based on a predetermined hierarchy ofoutcomes to generate an enhanced community health care database; andrepresenting one or more of the communities in association with one ormore corresponding outcome ranks assigned to a respective health careoutcome in the respective community.
 4. The method of claim 1, assigninga population attribute rank to each of the population attributes, andrepresenting one or more of the communities based on the ranking of oneor more of the population attributes associated with the respectivecommunities.
 5. The method of claim 1, comprising: computing acorrelation between selected health care outcomes with selectedpopulation attributes; and identifying similar communities based on aresult of the correlating.
 6. The method of claim 1 in which theplurality of health care outcomes include measures of health care cost,health care quality, and population health.
 7. The method of claim 1, inwhich the population attributes include measure of social capital,economics, demographics, behaviors, health care provider capacity,health care provider incentives, integration and alignment of healthcare providers, and information technology.
 8. A system for measuringhealth care related characteristics of a population segment using datadetermined from diverse data stores, comprising: one or more electronicdata storage systems coupled to one or more health care networks; acommunity health care database stored in the one or more electronic datastorage systems, the community database including a first collection ofhealth care data, the first collection including a plurality of healthcare outcomes for health care consumers in a plurality of communities,wherein the health care outcomes for each consumer are associated withone or more of the communities; a second collection of community datastored in the one or more electronic data storage systems, the secondcollection including a plurality of population attributes thatcharacterize the health care consumers in each of the communities; andone or more processors coupled in electronic communication with the oneor more electronic data storage systems, the one or more processorsconfigured for: receiving, by the processor, a first interactive inputthat selects one or more of the health care outcomes and/or one or moreof the population attributes, identifying, by the processor, acorrelation between the selected health care outcomes and one or more ofthe population attributes by accessing the first collection of healthcare data and the second collection of community data in response toreceiving the interactive inputs to provide correlated data, andprocessing, by the data processing system, the correlated data using acommunity measures tool, comprising: generating, by the communitymeasures tool, a visual representation of the correlated data to a user,the visual representation comprising a heat map representation of healthcare measures having a color coded or shaded grid identifying similarcommunities based on a result of the correlation; generating, by acommunity measures scoring tool of the community measures tool, acommunity score for the plurality of communities; receiving, by acomputer implemented application of the community measures tool,user-defined weights for one or more of the population attributes and/orone or more of the health care outcomes to customize the visualrepresentation and/or community score to the user, the applicationincluding a graphical user interface adapted to receive the user-definedweights; automatically updating, by the community measures tool, thevisual representation of the correlated data in response to changes tothe user-defined weights from the graphical user interface; receiving,by the community measures tool, a user input that selects one or more ofthe plurality of communities; and displaying, by the community measurestool, corresponding healthcare outcomes and population attributes of theselected communities from the selection of one or more of the pluralityof communities on the visual representation for comparison between eachcommunity.
 9. The system of claim 8, wherein the one or more processorsare configured to: assign, by the processor, a population attribute rankto each of the population attributes, and represent, by the processor,one or more of the communities based on the ranking of one or more ofthe population attributes associated with the respective communities.10. The system of claim 9, wherein the one or more processors areconfigured to: assign, by the processor, an outcome rank to each of thehealth care outcomes based on a predetermined hierarchy of outcomes togenerate an enhanced community health care database; and represent, bythe processor, one or more of the communities in association with one ormore corresponding outcome ranks assigned to a respective health careoutcome in the respective community.
 11. The system of claim 8, whereinthe one or more processors are configured to identify, by the processor,similar communities based on a result of the correlating.
 12. The systemof claim 8, wherein the one or more processors are configured tointeractively compute, by the processor, the correlation in response toreceiving the input.
 13. The system of claim 8, wherein the plurality ofhealth care outcomes include measures of health care cost, health carequality, and population health.
 14. The system of claim 8, wherein thepopulation attributes include measure of consisting of social capital,economics, demographics, population behaviors, health care providercapacity, health care provider incentives, integration and alignment ofhealth care providers, and health information technology.
 15. A methodimplemented on a data processing system measuring community health carecharacteristics using data determined from diverse data stores, themethod comprising: receiving, by the data processing system, one or morehealth care outcomes for each of a plurality of communities;automatically scoring, by the data processing system, each of thecommunities based on the corresponding health care outcomes; displaying,by the data processing system, a representation of the communitiesarranged based on their score; receiving, by the data processing system,one or more population attributes that characterize the health careconsumers in each of the plurality of communities; displaying, by thedata processing system, an indication of the corresponding populationattributes in the representation of the communities; receiving, by thedata processing system, an input that selects one or more of thepopulation attributes and one or more of the health care outcomes;generating, by the data processing, correlated data between the selectedpopulation attributes and the selected health care outcomes in responseto receiving the input; processing, by the data processing system, thecorrelated data using a community measures tool, comprising: generating,by the community measures tool, a visual representation of thecorrelated data to a user, the visual representation comprising a heatmap representation of health care measures having a color coded orshaded grid identifying similar communities based on a result ofcorrelation; generating, by a community measures scoring tool of thecommunity measures tool, a community score for the plurality ofcommunities; receiving, by a computer implemented application of thecommunity measures tool, user-defined weights for one or more of thepopulation attributes and/or one or more of the health care outcomes tocustomize the visual representation and/or community score to the user,the application including a graphical user interface adapted to receivethe user-defined weights automatically updating, by the communitymeasures tool, the visual representation of the correlated data inresponse to changes to the user-defined weights from the graphical userinterface; interactively displaying, by the data processing system, ageographical representation of a relationship between the selectedpopulation attributes and the selected-health care outcomes in responseto receiving the input; and receiving, by the community measures tool, auser input that selects one or more of the plurality of communities; anddisplaying, by the community measures tool, corresponding healthcareoutcomes and population attributes of the selected communities from theselection of one or more of the plurality of communities on the visualrepresentation for comparison between each community.
 16. The method ofclaim 15, comprising: receiving, by the data processing system, an inputthat selects a plurality of the population attributes; and interactivelydisplaying, by the data processing system, the heat map representationbased on the selected population attributes for each of a number ofcommunities in response to receiving the input.
 17. The method of claim16, comprising: generating, by the data processing system, clusteringinformation defining relationships between the displayed health caremeasures; and rearranging, by the data processing system, the heat maprepresentation based on the clustering information.
 18. A methodimplemented on a data processing system measuring community health careattributes using data determined from diverse data stores, the methodcomprising: storing, by the data processing system, a first collectionof community data in the one or more electronic data storage systems,the first collection including a plurality attributes that characterizehealth care consumers in each of a plurality of communities;associating, by the data processing system, the attributes thatcharacterize the health care consumers with one or more of thecommunities to generate a health care community population attributedatabase; receiving, by the data processing system, an input thatselects a first one of the attributes in a community and a second one ofthe attributes in the community; identifying, by the data processingsystem, a correlation between the first one of the attributes in acommunity and the second one of the attributes in the community byaccessing the health care community population attribute database toprovided correlated data; processing, by the data processing system, thecorrelated data using a community measures tool, comprising: generating,by the community measures tool, a visual representation of thecorrelated data to a user, the visual representation comprising a heatmap representation of health care measures having a color coded orshaded grid identifying similar communities based on a result of thecorrelation; generating, by a community measures scoring tool of thecommunity measures tool, a community score for the plurality ofcommunities; receiving, by a computer implemented application of thecommunity measures tool, user-defined weights for one or more of thepopulation attributes and/or one or more of the health care outcomes tocustomize the visual representation and/or community score to the user,the application including a graphical user interface adapted to receivethe user-defined weights; automatically updating, by the communitymeasures tool, the visual representation of the correlated data inresponse to changes to the user-defined weights from the graphical userinterface; receiving, by the community measures tool, a user input thatselects one or more of the plurality of communities; and displaying, bythe community measures tool, corresponding healthcare outcomes andpopulation attributes of the selected communities from the selection ofone or more of the plurality of communities on the visual representationfor comparison between each community.
 19. A method implemented on adata processing system measuring community attributes using datadetermined from diverse data stores, the method comprising: storing, bythe data processing system, a first collection of health care data inone or more electronic storage systems, the first collection including aplurality of health care outcomes for health care consumers in aplurality of communities; and associating, by the data processingsystem, the health care outcomes for each consumer with one or more ofthe communities to generate a community health care database; storing,by the data processing system, a second collection of community data inthe one or more electronic data storage systems, the second collectionincluding a plurality of population attributes that characterize thehealth care consumers in each of the communities; receiving, by the dataprocessing system, an input that selects one or more of the populationattributes and one or more of the health care outcomes; identifying, bythe data processing system, a correlation between a first one of thepopulation attributes and a second one of the population attributes toprovide correlated data; and processing, by the data processing system,the correlated data using a community measures tool, comprising:generating, by the community measures tool, a visual representation ofthe correlated data to a user, the visual representation comprising aheat map representation of health care measures having a color coded orshaded grid identifying similar communities based on a result of thecorrelation; generating, by a community measures scoring tool of thecommunity measures tool, a community score for the plurality ofcommunities; receiving, by a computer implemented application of thecommunity measures tool, user-defined weights for one or more of thepopulation attributes and/or one or more of the health care outcomes tocustomize the visual representation and/or community score to the user,the application including a graphical user interface adapted to receivethe user-defined weights; automatically updating, by the communitymeasures tool, the visual representation of the correlated data inresponse to changes to the user-defined weights from the graphical userinterface; receiving, by the community measures tool, a user input thatselects one or more of the plurality of communities; and displaying, bythe community measures tool, corresponding healthcare outcomes andpopulation attributes of the selected communities from the selection ofone or more of the plurality of communities on the visual representationfor comparison between each community.
 20. The method of claim 19wherein the plurality of outcomes are grouped into a plurality ofcategories, the categories comprising measures of health care cost,measures of health care quality, and measures of population health. 21.The method of claim 19, further comprising statistically processing theplurality of health care outcomes to generate a plurality of categoriesof health care outcomes.
 22. The method of claim 19, wherein thepopulation attributes are grouped into a plurality of categories, thecategories comprising measure of social capital, measures of economics,measures of demographics, measures of health behaviors, measures ofhealth care provider capacity, measures of health care providerincentives, measures of integration of health care providers, measuresof alignment of health care providers, and measures of healthinformation technology.
 23. The method of claim 19, further comprisingstatistically processing the plurality of population attributes togenerate a plurality of categories of population attributes.
 24. Themethod of claim 19, further comprising: and storing a second collectionof community data in the one or more electronic data storage systems,the second collection including a plurality of population attributesthat characterize the health care consumers in each of the communities;identifying a correlation between one or more of the health careoutcomes and one or more of the population attributes by accessing thefirst collection of health care data and the second collection ofcommunity data; and representing the correlation to a user.
 25. Themethod of claim 24, wherein the second collection further includes aplurality of population attributes that characterizes a system of healthcare, a health care infrastructure, and/or a health care environment ineach of the communities.
 26. The method of claim 24, further comprising:assigning an outcome score to each of the health care outcomes based ona predetermined hierarchy of outcomes; and computing a composite outcomescore for each community by statistically combining the outcome scoresin each respective community.
 27. The method of claim 26, furthercomprising: representing one or more of the communities based arespective composite outcome score of the respective communities. 28.The method of claim 26, further comprising: assigning a populationattribute score to each of the population attributes, and computing acomposite population attribute score for each community by statisticallycombining the population attribute scores in each respective community.29. The method of claim 28, further comprising: representing one or moreof the communities based on the composite population attribute score ofthe respective communities.
 30. The method of claim 28, furthercomprising: computing a community efficiency score by statisticallycomparing the composite population attribute score of the community withthe composite outcome score of the community.
 31. The method of 28,further comprising: computing community efficiency scores for each of aplurality of communities by statistically comparing the compositepopulation attribute score of each of the plurality of communities withthe composite outcome score of each respective one of the plurality ofcommunities; and displaying the community efficiency scores for each ofthe plurality of communities.
 32. The method of claim 28, comprising:displaying a geographical representation of a relationship betweenselected health care outcomes and/or selected population attributes. 33.The method of claim 28, comprising: displaying the heat maprepresentation based on selected health care outcomes and/or selectedpopulation attributes, the heat map representation including compositeoutcome score indication and/or a composite population attribute scoreindication for each of a plurality of the communities.
 34. The method ofclaim 33, comprising: computing clustering information that definesrelationships between the displayed health care measures; andrearranging the heat map representation based on the clusteringinformation.